Jazzer is a coverage-guided, in-process fuzzer for the JVM platform developed by [Code Intelligence](https://code-intelligence.com).
It is based on [libFuzzer](https://llvm.org/docs/LibFuzzer.html) and brings many of its instrumentation-powered mutation features to the JVM.
Jazzer currently supports the following platforms:
* Linux x86_64
* macOS 12+ x86_64 & arm64
* Windows x86_64
## Quick start
You can use Docker to try out Jazzer's Autofuzz mode, in which it automatically generates arguments to a given Java function and reports unexpected exceptions and detected security issues:
```
docker run -it cifuzz/jazzer-autofuzz \
com.mikesamuel:json-sanitizer:1.2.0 \
com.google.json.JsonSanitizer::sanitize \
--autofuzz_ignore=java.lang.ArrayIndexOutOfBoundsException
```
Here, the first two arguments are the Maven coordinates of the Java library and the fully qualified name of the Java function to be fuzzed in "method reference" form.
The optional `--autofuzz_ignore` flag takes a list of uncaught exception classes to ignore.
After a few seconds, Jazzer should trigger an `AssertionError`, reproducing a bug it found in this library that has since been fixed.
## Using Jazzer via...
### JUnit 5
The following steps assume that JUnit 5 is set up for your project, for example based on the official [junit5-samples](https://github.com/junit-team/junit5-samples).
1. Add a dependency on `com.code-intelligence:jazzer-junit:`.
All Jazzer Maven artifacts are signed with [this key](deploy/maven.pub).
2. Add a new *fuzz test* to a new or existing test class: a method annotated with [`@FuzzTest`](https://codeintelligencetesting.github.io/jazzer-docs/jazzer-junit/com/code_intelligence/jazzer/junit/FuzzTest.html) and at least one parameter.
Using a single parameter of type [`FuzzedDataProvider`](https://codeintelligencetesting.github.io/jazzer-docs/jazzer-api/com/code_intelligence/jazzer/api/FuzzedDataProvider.html), which provides utility functions to produce commonly used Java values, or `byte[]` is recommended for optimal performance and reproducibility of findings.
3. Assuming your test class is called `com.example.MyFuzzTests`, create the *inputs directory* `src/test/resources/com/example/MyFuzzTestsInputs`.
4. Run a fuzz test with the environment variable `JAZZER_FUZZ` set to `1` to let the fuzzer rapidly try new sets of arguments.
If the fuzzer finds arguments that make your fuzz test fail or even trigger a security issue, it will store them in the inputs directory.
5. Run the fuzz test without `JAZZER_FUZZ` set to execute it only on the inputs in the inputs directory.
This mode, which behaves just like a traditional unit test, ensures that issues previously found by the fuzzer remain fixed and can also be used to debug the fuzz test on individual inputs.
A simple property-based fuzz test could look like this (excluding imports):
```java
class ParserTests {
@Test
void unitTest() {
assertEquals("foobar", SomeScheme.decode(SomeScheme.encode("foobar")));
}
@FuzzTest
void fuzzTest(FuzzedDataProvider data) {
String input = data.consumeRemainingAsString();
assertEquals(input, SomeScheme.decode(SomeScheme.encode(input)));
}
}
```
A complete Maven example project can be found in [`examples/junit`](examples/junit).
### CI Fuzz
The open-source CLI tool [cifuzz](https://github.com/CodeIntelligenceTesting/cifuzz) makes
it easy to set up Maven and Gradle projects for fuzzing with Jazzer.
It provides a command-line UI for fuzzing runs, deduplicates and manages findings, and
provides coverage reports for fuzz tests. Moreover, you can use CI Fuzz to run your fuzz
tests at scale in the [CI App](https://app.code-intelligence.com).
### GitHub releases
You can also use GitHub release archives to run a standalone Jazzer binary that starts its own JVM configured for fuzzing:
1. Download and extract the latest release from the [GitHub releases page](https://github.com/CodeIntelligenceTesting/jazzer/releases).
2. Add a new class to your project with a public static void fuzzerTestOneInput(FuzzedDataProvider data) method.
3. Compile your fuzz test with `jazzer_standalone.jar` on the classpath.
4. Run the `jazzer` binary (`jazzer.exe` on Windows), specifying the classpath and fuzz test class:
```shell
./jazzer --cp= --target_class=
```
If you see an error saying that `libjvm.so` has not been found, make sure that `JAVA_HOME` points to a JDK.
The [`examples`](examples/src/main/java/com/example) directory includes both toy and real-world examples of fuzz tests.
### Docker
The "distroless" Docker image [cifuzz/jazzer](https://hub.docker.com/r/cifuzz/jazzer) includes a recent Jazzer release together with OpenJDK 17.
Mount a directory containing your compiled fuzz target into the container under `/fuzzing` and use it like a GitHub release binary by running:
```sh
docker run -v path/containing/the/application:/fuzzing cifuzz/jazzer --cp= --target_class=
```
If Jazzer produces a finding, the input that triggered it will be available in the same directory.
### Bazel
Support for Jazzer is available in [rules_fuzzing](https://github.com/bazelbuild/rules_fuzzing), the official Bazel rules for fuzzing.
See [the README](https://github.com/bazelbuild/rules_fuzzing#java-fuzzing) for instructions on how to use Jazzer in a Java Bazel project.
### OSS-Fuzz
[Code Intelligence](https://code-intelligence.com) and Google have teamed up to bring support for Java, Kotlin, and other JVM-based languages to [OSS-Fuzz](https://github.com/google/oss-fuzz), Google's project for large-scale fuzzing of open-souce software.
Read [the OSS-Fuzz guide](https://google.github.io/oss-fuzz/getting-started/new-project-guide/jvm-lang/) to learn how to set up a Java project.
## Further documentation
* [Common options and workflows](docs/common.md)
* [Advanced techniques](docs/advanced.md)
## Findings
A list of security issues and bugs found by Jazzer is maintained [here](docs/findings.md).
If you found something interesting and the information is public, please send a PR to add it to the list.
## Credit
The following developers have contributed to Jazzer before its public release:
[Sergej Dechand](https://github.com/serj),
[Christian Hartlage](https://github.com/dende),
[Fabian Meumertzheim](https://github.com/fmeum),
[Sebastian Pöplau](https://github.com/sebastianpoeplau),
[Mohammed Qasem](https://github.com/mohqas),
[Simon Resch](https://github.com/simonresch),
[Henrik Schnor](https://github.com/henrikschnor),
[Khaled Yakdan](https://github.com/kyakdan)
The LLVM-style edge coverage instrumentation for JVM bytecode used by Jazzer relies on [JaCoCo](https://github.com/jacoco/jacoco).
Previously, Jazzer used AFL-style coverage instrumentation as pioneered by [kelinci](https://github.com/isstac/kelinci).
[`FuzzedDataProvider`]: https://codeintelligencetesting.github.io/jazzer-docs/jazzer-api/com/code_intelligence/jazzer/api/FuzzedDataProvider.html
